New speech enhancement using Gamma tone filters and Perceptual Wiener filtering based on sub banding

Odugu, Kishore; Rao, B. M. S. Sreenivasa

doi:10.1109/icspcom.2013.6719789

Cited by 2 publications

(2 citation statements)

References 19 publications

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“…However, if the noise is not defined, identification and filtering thereof are essential; the adaptive Weiner filter (AWF) [9], spectral subtraction [10], and gamma-tone filter (GTF) [11] can be employed to this end. The AWF detects noise by reducing the difference between the filtered and intended signals.…”

Section: The Structure Of Voice Signalsmentioning

confidence: 99%

A Method of Evaluating Korean Articulation Quality for Rehabilitation of Articulation Disorder in Children

2020

KSII TIIS

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Articulation disorders are characterized by an inability to achieve clear pronunciation due to misuse of the articulators. In this paper, a method of detecting such disorders by comparing to the standard pronunciations is proposed. This method defines the standard pronunciations from the speeches of normal children by clustering them with three features which are the Linear Predictive Cepstral Coefficient (LPCC), the Mel-Frequency Cepstral Coefficient (MFCC), and the Relative Spectral Analysis Perceptual Linear Prediction (RASTA-PLP). By calculating the distance between the centroid of the standard pronunciation and the inputted pronunciation, disordered speech whose features locates outside the cluster is detected.89 children (58 of normal children and 31 of children with disorders) were recruited. 35 U-TAP test words were selected and each word's standard pronunciation is made from normal children and compared to each pronunciation of children with disorders. In the experiments, the pronunciations with disorders were successfully distinguished from the standard pronunciations.

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Section: The Structure Of Voice Signalsmentioning

confidence: 99%

A Method of Evaluating Korean Articulation Quality for Rehabilitation of Articulation Disorder in Children

2020

KSII TIIS

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“…The common methods to reduce noise include spectral subtraction, Wiener Filtering, Kalman filtering. Yet all of them have the problem of musical residual noise and low speech intelligibility for low input signal-to-noise ratios (SNR) [1].…”

Section: Introductionmentioning

confidence: 99%

A Multiband Noise Reduction Wiener Filter Algorithm for Hearing Aid

Xue

Guo

Wang

2015

AMM

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Speech processing in hearing aid often operates in noisy environments. So noise reduction algorithm is very important for hearing aid. This paper reviews conventional wiener filter algorithm and points out its remained problems----musical residual noise and low speech intelligibility for low input signal-to-noise ratios (SNR). To solve the problems, the proposed algorithm divides the frequency (0-8000 Hz) into 16 bands in Mel-frequency scale and processes the signal separately to remove musical residual noise. Meanwhile, a new Voice Activity Detector (VAD) applied for digital hearing aid is also presented. Based on the accurate judgment of speech frame, the filter processes the speech frame and non-speech frame in different ways. The method is realized in matlab to test output SNR and PESQ (Perceptual Evaluation of Speech Quality). It is also realized in android app for real-time test. Both of the experimental results demonstrate the advances of the proposed algorithm.

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New speech enhancement using Gamma tone filters and Perceptual Wiener filtering based on sub banding

Cited by 2 publications

References 19 publications

A Method of Evaluating Korean Articulation Quality for Rehabilitation of Articulation Disorder in Children

A Method of Evaluating Korean Articulation Quality for Rehabilitation of Articulation Disorder in Children

A Multiband Noise Reduction Wiener Filter Algorithm for Hearing Aid

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